The Neural Testbed: Evaluating Joint Predictions

The Neural Testbed: Evaluating Joint Predictions

9 October 2021

Vikranth Dwaracherla

Dieterich Lawson

Brendan O'Donoghue

Benjamin Van Roy

Papers citing "The Neural Testbed: Evaluating Joint Predictions"

19 / 19 papers shown

Title
Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling Daksh Mittal Ang Li Tzu-Ching Yen Daniel Guetta Hongseok Namkoong 45 0 0 03 Mar 2025
The Need for a Big World Simulator: A Scientific Challenge for Continual Learning Saurabh Kumar Hong Jun Jeon Alex Lewandowski Benjamin Van Roy 29 0 0 06 Aug 2024
Making Better Use of Unlabelled Data in Bayesian Active Learning Freddie Bickford-Smith Adam Foster Tom Rainforth 36 3 0 26 Apr 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 40 27 0 01 Feb 2024
Efficient Exploration for LLMs Vikranth Dwaracherla S. Asghari Botao Hao Benjamin Van Roy LLMAG 15 20 0 01 Feb 2024
Reducing LLM Hallucinations using Epistemic Neural Networks Shreyas Verma Kien Tran Yusuf Ali Guangyu Min 38 7 0 25 Dec 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Qianli Shen Wai Hoh Tang Zhun Deng Apostolos F. Psaros Kenji Kawaguchi 63 1 0 10 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 56 18 0 28 Sep 2023
Scalable Neural Contextual Bandit for Recommender Systems Zheqing Zhu Benjamin Van Roy OffRL 24 9 0 26 Jun 2023
Efficient Exploration via Epistemic-Risk-Seeking Policy Optimization Brendan O'Donoghue OffRL 27 6 0 18 Feb 2023
Approximate Thompson Sampling via Epistemic Neural Networks Ian Osband Zheng Wen S. Asghari Vikranth Dwaracherla M. Ibrahimi Xiuyuan Lu Benjamin Van Roy BDL 29 20 0 18 Feb 2023
Leveraging Demonstrations to Improve Online Learning: Quality Matters Botao Hao Rahul Jain Tor Lattimore Benjamin Van Roy Zheng Wen 21 8 0 07 Feb 2023
Fine-Tuning Language Models via Epistemic Neural Networks Ian Osband S. Asghari Benjamin Van Roy Nat McAleese John Aslanides G. Irving UQLM 31 16 0 03 Nov 2022
An Analysis of Ensemble Sampling Chao Qin Zheng Wen Xiuyuan Lu Benjamin Van Roy 26 22 0 02 Mar 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 52 56 0 23 Feb 2022
Deep Exploration for Recommendation Systems Zheqing Zhu Benjamin Van Roy 32 11 0 26 Sep 2021
Epistemic Neural Networks Ian Osband Zheng Wen M. Asghari Vikranth Dwaracherla M. Ibrahimi Xiyuan Lu Benjamin Van Roy UQCV BDL 30 97 0 19 Jul 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,660 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,136 0 06 Jun 2015